# but you must manually close the client session at the end of your program/event loop
aiosession = ClientSession()
tracer = LangChainTracer()
tracer.load_default_session()
manager = CallbackManager([StdOutCallbackHandler(), tracer])
# Pass the manager into the llm if you want llm calls traced.
llm = OpenAI(temperature=0, callback_manager=manager)
async_tools = load_tools(["llm-math", "serpapi"], llm=llm, aiosession=aiosession)
async_agent = initialize_agent(async_tools, llm, agent="zero-shot-react-description", verbose=True, callback_manager=manager)
await async_agent.arun(questions[0])
await aiosession.close()
> Entering new AgentExecutor chain...
 I need to find out who won the US Open men's final in 2019 and then calculate his age raised to the 0.334 power.
Action: Search
Action Input: "US Open men's final 2019 winner"
Observation: Rafael Nadal
Thought: I need to find out Rafael Nadal's age
Action: Search
Action Input: "Rafael Nadal age"
Observation: 36 years
Thought: I need to calculate 36 raised to the 0.334 power
Action: Calculator
Action Input: 36^0.334
Observation: Answer: 3.3098250249682484
Thought: I now know the final answer
Final Answer: Rafael Nadal, aged 36, won the US Open men's final in 2019 and his age raised to the 0.334 power is 3.3098250249682484.
> Finished chain.
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Conversation Agent (for Chat Models)
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Serial vs. Concurrent Execution